Contributors make recommendations on stocks taking into account various factors including predicted price appreciation. A contributor may include an analyst, a group of analysts, a brokerage firm, or other contributors. Contributors may convey their recommendations via a recommendation scheme. A recommendation scheme generally will include various-numbers of recommendation levels and a label for each level. For example, a simple three level recommendation scheme may include a positive, negative or neutral. A five level recommendation scheme may include a buy, a strong buy, a sell, a strong sell or a hold. More generally, a recommendation scheme may include one or more recommendations for predicted positive returns, a recommendation for returns that are predicted to be neutral, and one or more recommendations for predicted negative returns. A recommendation scheme may include recommendations relative to a benchmark such as an overweight recommendation for predicted positive returns, an inline recommendation for predicted neutral returns, and an underweight recommendation for predicted negative returns. Other recommendation schemes and labels are known.
For simplicity, as used herein three level recommendation schemes may be generically represented as including a positive recommendation, a neutral recommendation, and a negative recommendation, and five level recommendation schemes may be generically represented as including a more positive recommendation, a positive recommendation, a neutral recommendation, a negative recommendation, and a more negative recommendation. Except as specifically indicated otherwise, this is not intended to exclude other labels.
Different contributors may use recommendation schemes that seem similar based on labels, but may actually correspond to different benchmark-relative returns. For example, a first contributor may use a five level recommendation scheme. A second contributor may use a three level recommendation scheme wherein a positive recommendation corresponds to a predicted benchmark-relative return similar to that of a positive recommendation in the five level recommendation scheme of the first recommendation, and a negative recommendation corresponds to a benchmark-relative return similar to that of a negative recommendation in the five level recommendation scheme of the first contributor. A third contributor may use a three level recommendation scheme wherein a positive recommendation corresponds to a benchmark-relative return similar to that of a more positive recommendation in the five level recommendation scheme of the first contributor, and a negative recommendation corresponds to a benchmark-relative return similar to that of a more negative recommendation in the five level recommendation scheme of the first contributor. In other words, if a five-level scheme has ratings 1-5 (from most positive to most negative) a three level scheme may correspond to levels 1, 3, 5 or it may correspond to 2, 3, 4.
Different contributors may make recommendations based on predictions of benchmark-relative returns that are relative to different benchmarks. Benchmarks may be fixed benchmarks or variable benchmarks. For example, a fixed benchmark may be 5% for a positive and 15% for a more positive at one contributor and other percentages for another contributor. Variable benchmarks may be a market index benchmark related to stock valuations of stocks associated with a market index, an industry benchmark related to stock valuations of stocks within a given industry, or other variable benchmarks.
Various methods exist for measuring the performance of a contributor on all or a large number of stocks via a portfolio calculation approach. These systems typically create a simulated portfolio for a set (e.g., those in an industry classification) of each contributors stocks where the portfolio mimics owning “positive-rated” stocks and shorting negative-rated stocks. These systems may not answer the question of which contributor is best at rating a single stock. Further, these systems may merely yield a possible percent return, and not a score representative of an accuracy of the analyst in predicting future stock valuation. Moreover, a percent return alone can be misleading, depending on the performance of other stocks or benchmarks. These systems usually require a minimum number of stocks followed in the set (e.g., semiconductor industry) to be scored and ranked on that set. In known systems, stocks that have little variation in value may be difficult to compare with other stocks, or they may not take into account separate benchmarks for separate stocks.
Another drawback of existing systems is how to evaluate a neutral recommendation. In a percent return analysis a neutral rating may yield little “return” but may be a very good prediction. Other problems and drawbacks also exist.
Therefore, there exists a need for scoring a contributor for the performance of recommendations by the analyst or analysts with respect to a single stock.